Network Analysis

Instructor(s):

Ann McCranie, Indiana University

Social network analysis (SNA) focuses on relationships between social entities. It is used widely in the social and behavioral sciences, as well as in political science, economics, organizational science, and industrial engineering. The social network perspective, which will be taught in this workshop, has been developed over the last seventy years by researchers in psychology, sociology, political science, and anthropology. New interest in this field by physics, information science, social media studies, and biomedical fields has spiked in the past 15 years - this approach is often referred to as "network science." While this approach sometimes differs importantly in scale and substantive interest, it is often used to study the exact same problems as traditional SNA. This course will connect these two traditions in their terminology and specific methodological approaches.

This four-week workshop covers precisely those SNA concepts and tools. It will present an introduction to various concepts, methods, and applications of social network analysis drawn from the social and behavioral sciences. The primary focus of these methods is the analysis of relational data measured on groups of social actors. Topics to be discussed include a basic introduction to SNA, graphs and matrices, basic network measures and visualization, reciprocity and transitivity, dyadic and triadic analysis, centrality, egocentric networks, two-mode networks (affiliations, bibliographic/scientometric analysis), cohesive subgroups, equivalences and blockmodeling, hubs & authorities, cores & peripheries, clustering and graph partitioning, large scale structure of networks, statistical modeling in network (ergm/p*/RSiena), and network dynamics and change in networks. There should also be time for specific topics of participant interest.

Please note: The focus on statistical models (ergm/p*/Siena models) is limited and introductory in this course - those are the explicit focus of the advanced course offered in the second session. Also, this course focuses largely on "whole" or "complete" networks in which sociomentric analysis is required. Egocentric analysis is not a primary focus of this course, but will be a topic of discussion and inclusion when appropriate with the rest of the course.